Embodiments of the inventive subject matter generally relate to the field of data organization, and more particularly to presenting complex associations between various data fields.
With complex data sets, organizing the data into tables, charts, diagrams, etc. is often helpful in interpreting the data. Specifically, many tables, charts, diagrams, etc. ease the process of analyzing associations between various data fields. Data sets containing multiple data fields can include a collection of photographs, a collection of music, statistics relating to business, scientific research, etc.
A collection of photographs may have several data fields, such as a photograph number, location the photograph was taken, date the photograph was taken, and the people that are in the photograph. Additionally, a single person, date, or location can be associated with more than one photograph. To explore the relationships between the different data fields, charts can be organized into various configurations. For example, to analyze the association between the people in the photographs and the other various data fields, a table can be configured with the left-most column containing the names of individuals in the collection of photographs. Subsequent rows to the right of the “names” column may then contain additional information, such as photograph number, location, and date. This configuration provides useful information sorted by person. It however does not provide information about other associations as readily, e.g. the association between date and location.
Pivot tables can be utilized to aid in analyzing the relationship between various data fields. Unlike a static table, a pivot table is dynamic, and can be reconfigured to sort data sets based on selected parameters. As such, pivot tables allow the resorting of data to understand relationships between the various data fields. For example, a pivot table sorting by name can be reconfigured to be sorted by location, etc.